Change deepspeed installation (#3639)

Author: ZailiWang

examples/cpu/llm/Dockerfile

@@ -43,7 +43,7 @@ COPY . ./intel-extension-for-pytorch
 RUN . ~/miniforge3/bin/activate && conda create -y -n compile_py310 python=3.10 && conda activate compile_py310 && \
     cd intel-extension-for-pytorch/examples/cpu/llm && \
     export CC=gcc && export CXX=g++ && \
-    if [ -z ${COMPILE} ]; then bash tools/env_setup.sh 14; else bash tools/env_setup.sh 10; fi && \
+    if [ -z ${COMPILE} ]; then bash tools/env_setup.sh 6; else bash tools/env_setup.sh 2; fi && \
     unset CC && unset CXX
 
 FROM base AS deploy
@@ -60,7 +60,7 @@ COPY --from=dev /root/intel-extension-for-pytorch/tools/get_libstdcpp_lib.sh ./l
 RUN . ~/miniforge3/bin/activate && conda create -y -n py310 python=3.10 && conda activate py310 && \
     cd /usr/lib/x86_64-linux-gnu/ && ln -s libtcmalloc.so.4 libtcmalloc.so && cd && \
     cd ./llm && \
-    bash tools/env_setup.sh 9 && \
+    bash tools/env_setup.sh 1 && \
     python -m pip cache purge && \
     mv ./oneCCL_release /opt/oneCCL && \
     chown -R root:root /opt/oneCCL && \

examples/cpu/llm/README.md

@@ -7,29 +7,71 @@ And a set of data types are supported for various scenarios, including FP32, BF1
 
 # 2. Environment Setup
 
-**Note**: The instructions in this section will setup an environment with a recent PyTorch\* nightly build and **a latest source build of IPEX**. 
-If you would like to use stable PyTorch\* and IPEX release versions, please refer to the instructions [in the release branch](https://github.com/intel/intel-extension-for-pytorch/blob/v2.6.0%2Bcpu/examples/cpu/llm/README.md#2-environment-setup),
-in which IPEX is installed via prebuilt wheels using `pip install` rather than source code building.
+## 2.1 [RECOMMENDED] Docker-based environment setup with pre-built wheels
 
-**Note**: Please be aware that in order to enable the latest optimizations for MoE models (DeepSeek, Mixtral, etc.) in `DeepSpeed`,
-we are setting a different argument for `env_setup.sh` in IPEX v2.6.0+cpu comparing with previous versions,
-in order to build `DeepSpeed` from source code with a recent commit.
+```bash
+# Get the Intel® Extension for PyTorch\* source code
+git clone https://github.com/intel/intel-extension-for-pytorch.git
+cd intel-extension-for-pytorch
+git checkout v2.7.0+cpu
+git submodule sync
+git submodule update --init --recursive
+
+# Build an image with the provided Dockerfile by installing from Intel® Extension for PyTorch\* prebuilt wheel files
+# To have a custom ssh server port for multi-nodes run, please add --build-arg PORT_SSH=<CUSTOM_PORT> ex: 2345, otherwise use the default 22 SSH port
+DOCKER_BUILDKIT=1 docker build -f examples/cpu/llm/Dockerfile --build-arg PORT_SSH=2345 -t ipex-llm:2.7.0 .
+
+# Run the container with command below
+docker run --rm -it --privileged -v /dev/shm:/dev/shm ipex-llm:2.7.0 bash
+
+# When the command prompt shows inside the docker container, enter llm examples directory
+cd llm
+
+# Activate environment variables
+# set bash script argument to "inference" or "fine-tuning" for different usages
+source ./tools/env_activate.sh [inference|fine-tuning]
+```
+
+## 2.2 Conda-based environment setup with pre-built wheels
+
+```bash
+# Get the Intel® Extension for PyTorch\* source code
+git clone https://github.com/intel/intel-extension-for-pytorch.git
+cd intel-extension-for-pytorch
+git checkout v2.7.0+cpu
+git submodule sync
+git submodule update --init --recursive
+
+# GCC 12.3 is required. Installation can be taken care of by the environment configuration script.
+# Create a conda environment
+conda create -n llm python=3.10 -y
+conda activate llm
+
+# Setup the environment with the provided script
+cd examples/cpu/llm
+bash ./tools/env_setup.sh 7
+
+# Activate environment variables
+# set bash script argument to "inference" or "fine-tuning" for different usages
+source ./tools/env_activate.sh [inference|fine-tuning]
+```
 
-## 2.1 [Recommended] Docker-based environment setup with compilation from source
+## 2.3 Docker-based environment setup with compilation from source
 
 ```bash
 # Get the Intel® Extension for PyTorch\* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
+git checkout v2.7.0+cpu
 git submodule sync
 git submodule update --init --recursive
 
 # Build an image with the provided Dockerfile by compiling Intel® Extension for PyTorch\* from source
 # To have a custom ssh server port for multi-nodes run, please add --build-arg PORT_SSH=<CUSTOM_PORT> ex: 2345, otherwise use the default 22 SSH port
-docker build -f examples/cpu/llm/Dockerfile --build-arg COMPILE=ON --build-arg PORT_SSH=2345 -t ipex-llm:main .
+docker build -f examples/cpu/llm/Dockerfile --build-arg COMPILE=ON --build-arg PORT_SSH=2345 -t ipex-llm:2.7.0 .
 
 # Run the container with command below
-docker run --rm -it --net host --privileged -v /dev/shm:/dev/shm ipex-llm:main bash
+docker run --rm -it --net host --privileged -v /dev/shm:/dev/shm ipex-llm:2.7.0 bash
 
 # When the command prompt shows inside the docker container, enter llm examples directory
 cd llm
@@ -39,12 +81,13 @@ cd llm
 source ./tools/env_activate.sh [inference|fine-tuning]
 ```
 
-## 2.2 Conda-based environment setup with compilation from source
+## 2.4 Conda-based environment setup with compilation from source
 
 ```bash
 # Get the Intel® Extension for PyTorch\* source code
 git clone https://github.com/intel/intel-extension-for-pytorch.git
 cd intel-extension-for-pytorch
+git checkout v2.7.0+cpu
 git submodule sync
 git submodule update --init --recursive
 
@@ -55,7 +98,7 @@ conda activate llm
 
 # Setup the environment with the provided script
 cd examples/cpu/llm
-bash ./tools/env_setup.sh 11
+bash ./tools/env_setup.sh 3
 
 # Activate environment variables
 # set bash script argument to "inference" or "fine-tuning" for different usages